Glad to have your aid, Eftiquar.
> On May 22, 2018, at 12:17 PM, Shaikh, Eftiquar wrote:
>
> Hi Naveen,
> I can fill in for Windows expertise. Do we have approximate estimates on how
> long will it take to provide basic support.
>
> Best
> Eftiquar
>
+1 to pushing to the branch. We can revisit a patch release if there are
critical bugs.
On Tue, May 22, 2018 at 1:51 PM, Anirudh wrote:
> I think pushing the fixes back to the release branch should be sufficient.
> I am not sure why we need to maintain a different patches
I think pushing the fixes back to the release branch should be sufficient.
I am not sure why we need to maintain a different patches branch. I agree
that if there are a bunch of important fixes that didn't go into the
release, then we need to do a patch release for the same.
On Tue, May 22, 2018
1.2.1 patch release with this bug fix (+ others if applicable) will be very
useful for the users.
On Tue, May 22, 2018 at 1:08 PM, Rahul Huilgol
wrote:
> Maybe we could do that now, after the code for the release has been voted
> on. We could maintain a patches branch
Maybe we could do that now, after the code for the release has been voted
on. We could maintain a patches branch for a release. This would also be
helpful for users who are using a particular release version but hesitate
to switch to the latest release when it's out because of the many changes.
Hi Aaron,
Thanks for your work on this! Few points I noticed
1. Looks like something is wrong with the pip instructions. I see
instructions for pre-reqs but not the actual pip install.
2. Most of the language bindings seem to be redirects to install page for
that OS, regardless of CPU/GPU, but
done.
On Tue, May 22, 2018 at 12:30 PM, Wellner, Benjamin R.
wrote:
> Hello,
>
> I have just joined the Apache MXNet mailing list and would like to receive
> access to the MXNet Slack channel.
>
> Thanks,
>
> * Ben
>
Hello,
I have just joined the Apache MXNet mailing list and would like to receive
access to the MXNet Slack channel.
Thanks,
* Ben
Ultimately, I want to retire the version selector that swaps out the whole
site. Version selection can be at the API docs and at the install page where
people would expect to have that option.
Side note, because this come up when mentioning removal of the versions
dropdown for the site:
Hi Naveen,
I can fill in for Windows expertise. Do we have approximate estimates on how
long will it take to provide basic support.
Best
Eftiquar
From: Naveen Swamy
Sent: Tuesday, May 22, 2018 11:45 AM
To: d...@mxnet.apache.org
Hi team.
Flaky test failures are impacting PR validation and hindering contributions
to MXNet.
We should prioritize dealing with these failing tests.
See recent failures on master:
http://jenkins.mxnet-ci.amazon-ml.com/job/incubator-mxnet/job/master/
The biggest offenders right now:
Thanks Aaron for this quick preview.
Version is selected at the top level documentation? Should we show how to
install v1.0 when the user is viewing v1.2 docs?
>From UX functionality perspective - MXNet installation page is similar to
PyTorch? Collection of choices to make.
Behind the scenes,
MXNet UI definitely needs more love.
+1 - pytorch style
+0.5 - caffe2
On Tue, May 22, 2018 at 11:48 AM, Markham, Aaron
wrote:
> Hi everyone,
> In addition to the options on the wiki (pros & cons), there's this preview.
> It uses a dropdown next to the install options to
Hi everyone,
In addition to the options on the wiki (pros & cons), there's this preview.
It uses a dropdown next to the install options to make it clearer what versions
you can install… then updates the pip commands…
http://54.210.6.225/install/index.html#
Thoughts?
On 5/16/18, 9:31 AM,
I need to call `cpuinfo_processors_count`. The 8 files needed are below:
https://github.com/pytorch/cpuinfo/blob/master/src/api.c#L16
https://github.com/pytorch/cpuinfo/blob/master/src/api.h
https://github.com/pytorch/cpuinfo/blob/master/src/x86/windows/init.c#L569
Sorry for incomplete email. Sent it too fast.
Thanks for all the comments. Aaron guessed it right. We can treat it as a
multi-label classification problem. :)
We are currently working on the design document, will share it on dev list
once it is more concrete.
@Marco, seems like a good idea too
Thanks for all the comments. Aaron guessed it right. We can treat it as a
multi-label classification problem. :)
We are currently working on the design document, will share it on dev list
once it is more concrete.
@Marco, seems like a good idea too but as you said, it will still involve
manual
This is great. Thanks to everybody involved.
On Tue, May 22, 2018, 9:15 AM sandeep krishnamurthy wrote:
> Hello MXNet community,
>
> Keras users can now use the high-performance MXNet deep learning engine for
> the distributed training of convolutional neural networks (CNNs)
Hello MXNet community,
Keras users can now use the high-performance MXNet deep learning engine for
the distributed training of convolutional neural networks (CNNs) and
recurrent neural networks (RNNs). With an update of a few lines of code,
Keras developers can increase training speed by using
I am working to publish the full package for the 3 platforms that also
contains infer package. Spark package does not have any tests at the
moment. I think it needs some testing before we can publish to maven.
On Mon, May 21, 2018 at 9:19 PM, Hagay Lupesko wrote:
> +1 for a
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